Given a simple polygon P, the minimum convex cover problem seeks to cover P with the fewest convex polygons that lie within P. The maximum hidden set problem seeks to place within P a maximum cardinality set of points no two of which see each other. We give constant factor approximation algorithms for both problems. Previously, the best approximation factor for the minimum convex cover was logarithmic; for the maximum hidden set problem, no approximation algorithm was known.

This paper explores tradeoffs between ground impact and efficiency of drone flights in urban scenarios. We give an algorithm which produces a set of routes with different lengths and varying number of people affected by the drone. We also present an interactive online visualization tool allowing the user to modify flightpaths in order to explore routing options. Our path finder and the GUI are implemented for a metropolitan area of Norrköping municipality in Sweden. The methods studied in this paper may give UTM service provider the tools to negotiate flightplans which will be acceptable by both the regulator and the drone operator.

Specific Operations Risk Assessment (SORA) is a qualitative methodology for assessing risks of drone operations. In this paper, SORA is compared to and complemented with quantitative estimations of the risk (earlier called HFRM: High-fidelity risk modeling). We highlight intrinsic shortcomings of both SORA and HFRM, and show how HFRM may help to deal with SORA’s ambiguities. (We do not have a recipe to remedy HFRM’s drawbacks with the help of SORA, but suggest a possible regulatory fix to HFRM, addressing its deficiency.) With its focus on ground risk, this paper complements the works of TU Dresden which suggested integrating “agent simulation as air risk assessment in SORA” [Fricke et al., ATM Seminar 2021] and of SESAR’s ER4 BUBBLES project “proposing a quantitative risk analysis which enhances or replaces the qualitative model of SORA” (also for the air risk) [BUBBLES Deliverable 4.1]; we also connect to CORUS observations on SORA shortcomings and use U-space services for addressing them. Our work advocates for stricter regulations, including digitalization and automation not only in definitions, but also in mandates/requirements. Our arguments are illustrated on simple synthetic cases and on real-world experimental examples from urban areas.

We give algorithms for splitting a geographical region into ”approximately flat” rectangular zones. Each zone is assigned a feasible flight altitude, providing simple flight level guidance for future operations of unmanned aerial systems in low-level airspace. We consider a rural scenario with uneven ground level and an urban setting featuring many tall structures. In both cases, our solutions adapt to the underlying terrain or city landscape. In the rural scenario, operating on a fixed altitude within a rectangle allows the drone to stay within the upper limit of 120m while not flying too close to the ground; our objective is to minimize the complexity of the airspace. In the urban case, we aim at minimizing the volume of airspace reserved for drone operations, while allowing overflight over tall buildings in the city. Experiments with real landscape and city skyline data demonstrate output of our solutions with various input parameters.

We present a mixed-integer programming (MIP) approach to compute aircraft arrival routes in a terminal maneuvering area (TMA) that guarantee temporal separation of all aircraft arriving within a given time period, where the aircraft are flying according to the optimal continuous descent operation (CDO) speed profile with idle thrust. The arrival routes form a merge tree that satisfies several operational constraints, e.g., all merge points are spatially separated. We detail how the CDO speed profiles for different route lengths are computed. Experimental results are presented for calculation of fully automated CDO-enabled arrival routes during one hour of operation on a busy day at Stockholm TMA.

We consider paths with low exposure to a 2D polygonal domain, i.e., paths which are seen as little as possible; we differentiate between integral exposure (when we care about how long the path sees every point of the domain) and 0/1 exposure (just counting whether a point is seen by the path or not). For the integral exposure, we give a PTAS for finding the minimum-exposure path between two given points in the domain; for the 0/1 version, we prove that in a simple polygon the shortest path has the minimum exposure, while in domains with holes the problem becomes NP-hard. We also highlight connections of the problem to minimum satisfiability and settle hardness of variants of planar min- and max-SAT.

This work presents an enhanced optimization framework for fully automated scheduling of energy-efficient continuous-descent arrivals with guaranteed separation in the Terminal Maneuvering Area (TMA). On the example of a real heavy-traffic scenario at Stockholm Arlanda airport, we demonstrate that our approach enables scheduling of all planned arrivals during one hour of operation as continuous descents, by allowing flexible time of arrival to entry points within a range of ± 5 minutes. This provides significant savings in the time aircraft spend inside the TMA and a reduced fuel consumption. In addition, we integrate different aircraft wake turbulence categories that enable category-specific separation criteria. 

An important step towards improving the flight performance within Terminal Maneuvering Area (TMA) is the identification of the factors causing inefficiencies. Without knowing which exact factors have high impact on which performance indicators, it is difficult to identify which areas could be improved. In this work, we quantify the flight efficiency using average additional time in TMA, average time flown level and additional fuel consumption associated with the inefficient flight profiles. We apply statistical learning methods to assess the impact of different weather phenomena on the arrival flight efficiency, taking into account the current traffic situation. We utilize multiple data sources for obtaining both historical flight trajectories and historical weather measurements, which facilitates a comprehensive analysis of the variety of factors influencing TMA performance. We demonstrate our approach by identifying that wind gust and snow had the most significant impact on Stockholm Arlanda airport arrivals in 2018